Federated Model Distillation with Noise-Free Differential Privacy
Authors: Lichao Sun, Lingjuan Lyu | Published: 2020-09-11 | Updated: 2021-05-21
Second Order Optimization for Adversarial Robustness and Interpretability
Authors: Theodoros Tsiligkaridis, Jay Roberts | Published: 2020-09-10
Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning
Authors: Yang Zou, Zhikun Zhang, Michael Backes, Yang Zhang | Published: 2020-09-10
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent
Authors: Ricardo Bigolin Lanfredi, Joyce D. Schroeder, Tolga Tasdizen | Published: 2020-09-10 | Updated: 2023-04-20
A black-box adversarial attack for poisoning clustering
Authors: Antonio Emanuele Cinà, Alessandro Torcinovich, Marcello Pelillo | Published: 2020-09-09 | Updated: 2021-11-10
SoK: Certified Robustness for Deep Neural Networks
Authors: Linyi Li, Tao Xie, Bo Li | Published: 2020-09-09 | Updated: 2023-04-12
Attribute Privacy: Framework and Mechanisms
Authors: Wanrong Zhang, Olga Ohrimenko, Rachel Cummings | Published: 2020-09-08 | Updated: 2021-05-11
Highly Accurate CNN Inference Using Approximate Activation Functions over Homomorphic Encryption
Authors: Takumi Ishiyama, Takuya Suzuki, Hayato Yamana | Published: 2020-09-08 | Updated: 2020-12-02
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
Authors: Mohammad Naseri, Jamie Hayes, Emiliano De Cristofaro | Published: 2020-09-08 | Updated: 2022-05-27
Adversarial Attack on Large Scale Graph
Authors: Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng | Published: 2020-09-08 | Updated: 2021-05-06